* add activation

* update activation_op

* add unitest for activation

* fix acosh for init, test=develop

* conv_transpose_eltwiseadd_bn_fuse_pass

* change timeout

* add TIMEOUT

* add random num for group and dilation

* change PassCompat

* add test for conv_elementwise_add2_act_fuse_pass and conv_elementwise_add_act_fuse_pass

* Add conv_eltwiseadd_bn_fuse_pass test and fix test_conv_elementwise_addX_act_fuse_pass

* add tests for conv_act_mkldnn_fuse_pass

* add test for conv_bias_mkldnn_fuse_pass

* update code

* add conv_act_mkldnn_fuse_pass for relu, relu6, swish, leaky_relu

* update test

* update

* update bug

* update

* update pattern_detector

* fix test_conv_eltwiseadd_bn_fuse_pass

* add diff display notest;test=windows_ci_inference

* fix

* remove test_conv_act_mkldnn_fuse_pass.py

* ifix

* support eager switch system

* polish code

Add elementwise_fmax and elementwise_fmin operators

Add key_padding_mask and attn_mask in sparse_attention Api

1.Key padding mask is a tensor with dimensions [batch_size, seq_len], and attention mask is a tensor with dimensions [seq_len, seq_len]. The data types of the two masks are consistent with Q, K, and V, which are float32 or float64. If the value in Mask is 0, it means that the position needs to be masked.

2.The changed files are mainly paddle/fluid/operators/sparse_attention_op.cu and python/paddle/fluid/tests/unittests/test_sparse_attention_op.py. sparse_attention has three parts: sddmm, softmax, and dsd. Adding the mask operation only needs to modify the softmax. It has no effect on the other two parts. In addition, in order to test the mask function, related tests has been added.

* Add float16 type for scatter op.

* Add fp16 test for scatter op.

* Add int and int64 support for scatter_grad on gpu.

* Add int and int64 for check_variable_and_dtype routine.

* Minors.

* Code format.

* update mkldnn scale_matmul fuse pass ut

* update mkldnn scale_matmul_fuse_pass ut

* add mkldnn conv3d_bias_mkldnn_fuse_pass ut

* update conv3d_bias_mkldnn_fuse_pass ut

* disable conv3d_bias_mkldnn_fuse_pass

* fix bugs in Translated layer when change train/eval

* fix python converage

* fix error when tensor_shape_transformer. Before in stmt like `if len(paddle.shape(x)[0]) > 0`, `paddle` will be used as a variable

* handle other call like `fluid.layers.mean` and `fluid.layers.shape`

* add unit test

* add hinge_embedding_loss

* fix test_API

* test_API succeed

* add English doc

* fixed using of expired fluid api

* fix doc

* fix doc and rm python/paddle/fluid/layers/loss.py

* get raw python/paddle/fluid/layers/loss.py back

* fix Examples bug in English doc

* unique -> flatten

* fix api code

* fix English doc

* fix functional loss English doc

* fix Example doc

* .numpy() -> paddle.unique()

* fix unique

* fix label_item_set

* modified judgment equation

* Got a beautiful loss equation

* use paddle.to_tensor

* fix loss and add static check

* fix loss and add static check

* delta -> margin

* update mkldnn conv_concat_relu_mkldnn_fuse_pass ut

* update conv_concat_relu_mkldnn_fuse_pass ut

* restrict conv2d data_format in conv_concat_relu_mkldnn_fuse_pass

* add new API:paddle.movedim/moveaxis

* add new API:paddle.movedim/moveaxis

* add new API:add new API:paddle.movedim/moveaxis

* fix comment

* fix comment

* Enhance error msg in paddle.assign in static mode

* fix unittest

* add map_matmul passes to quant2_int8_mkldnn_pass

* fix fc+act fuse (activation scale)

* ci fix, c++17 structured bindings not available

* fix ci static check

* update Planner

* update unitest

* update PlanSpace

* update PlanSpace

* modify set_grad_var_shape

* update code style

* add conv_gelu_mkldnn_fuse_pass

* add post ops

* layer.to api support numpy.dtype and paddle.dtype

* skip the layer to eaxmple code executing for env not support

* Reduce reshape kernel functions in pten

* delete notes

* fix bugs when compile

* test_mkldnn_depthwise_conv_pass

* test: add TimeOut

* sset TIMEOUT

* fix:add random num for dilation and group

* add layer_norm_fuse_pass test case

* restore cmakelist code

* Merge branch 'develop' into layer_norm_fuse_pass

* Merge branch 'develop' into layer_norm_fuse_pass

* add bad case test